Detecting Anomalous Sensor Events in Smart Home Data for Enhancing the Living Experience

Vikramaditya Jakkula, Diane Cook

Last modified: 2011-08-24

Abstract

The need to have a secure lifestyle at home is in demand more than ever. Today’s home is more than just four walls and a roof. Technology at home is on the rise and the place for smart home solutions is growing. One of the major concerns for smart home systems is the capability of adapting to the user. Personalizing the behavior of the home may provide improved comfort, control, and safety. One of the challenges of this goal is tackling anomalous events or actions. This work proposes using machine learning techniques to address this issue of detecting anomalous events or actions in smart environment datasets. The approaches are validated using real-world sensor data captured from a smart home testbed.